Vector computing is a technique that entails executing a single operation while operating on collections of multiple elements or elements in arrays, or “vectors”, with that single operation. A vector may be characterized as a list of elements (or “operands”) processed by an operation. So, a single operation can be executed once with multiple operands, within machine architectures designed to perform vector computing. For example, if 6 numbers were to be repetitively added together within a program via a loop programming construct; then, rather than executing the addition operation multiple times, a vector processor could arrange to process a single addition operation at execution on all 6 numbers at once. This provides processor efficiency and increases operational throughput.
The benefits of vector processing include: 1) a reduced number of instructions needed to perform an operation on multiple operands; 2) each vector instruction may indicate operand dependency to processing logic, which the processing logic may exploit to increase processing performance; and 3) vector processing enables greater parallel processing of data.
A “mask” vector having the same number of elements as a vector instruction's operands, can be used to specify which of the elements of the vector operands should be operated on. This is especially beneficial when performing applications code with conditional statements using vector computing.
One challenge with vector processing is in the area of memory operations, such as vector loads addressing virtual paged memory. In this case one or more of the operands may not be available in memory for the processor to handle at the time the operation is executed. With such a situation, the processor flushes its contents (restarts) and attempts to acquire the missing operand and then attempts to process the operation again.
In virtual paged memory systems, the actual physical memory in the system may be over-subscribed and pages that do not fit in the physical memory system may be stored elsewhere, such as on a hard-drive. When a page is needed that is not currently in the physical memory, it may need to be acquired from the hard-drive, for example, which can adversely affect processing performance.
Since the element in a vector can be read from multiple locations in memory, a common situation may entail several restarts before an operation is successfully processed. This happens when elements that are loaded into a vector are located in different physical pages that need to be acquired. However, during each restart the processor is not making any forward progress on the operation. That is, no results or running results are available until the operation successfully processes with all the operands at once. Further, the process of acquiring additional elements may displace the first elements acquired. Hence, we need a system of incrementally completing the operation, so that forward progress and efficient processing is guaranteed.
The current invention allows a novel and efficient handling of the progress that is done for each attempt to execute a vector operation.